Donglin Fan
Orcid: 0000-0002-2100-6634
According to our database1,
Donglin Fan
authored at least 18 papers
between 2020 and 2024.
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Bibliography
2024
Estimation and trend analysis of carbon emissions from forest fires in mainland China from 2011 to 2021.
Ecol. Informatics, 2024
Estimation of daytime all-sky sea surface temperature from Himawari-8 based on multilayer stacking machine learning.
Int. J. Appl. Earth Obs. Geoinformation, 2024
Synergistic retrieval of mangrove vital functional traits using field hyperspectral and satellite data.
Int. J. Appl. Earth Obs. Geoinformation, 2024
Proceedings of the IGARSS 2024, 2024
2023
Comparison of 2D and 3D vegetation species mapping in three natural scenarios using UAV-LiDAR point clouds and improved deep learning methods.
Int. J. Appl. Earth Obs. Geoinformation, December, 2023
Quantifying scattering characteristics of mangrove species from Optuna-based optimal machine learning classification using multi-scale feature selection and SAR image time series.
Int. J. Appl. Earth Obs. Geoinformation, August, 2023
Classification of Citrus Huanglongbing Degree Based on CBAM-MobileNetV2 and Transfer Learning.
Sensors, 2023
2022
Assessment of Grassland Degradation on the Tibetan Plateau Based on Multi-Source Data.
Remote. Sens., December, 2022
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2022
Combination of Hyperspectral and Quad-Polarization SAR Images to Classify Marsh Vegetation Using Stacking Ensemble Learning Algorithm.
Remote. Sens., 2022
Comparison of Different Transfer Learning Methods for Classification of Mangrove Communities Using MCCUNet and UAV Multispectral Images.
Remote. Sens., 2022
Evaluation of Decision Fusions for Classifying Karst Wetland Vegetation Using One-Class and Multi-Class CNN Models with High-Resolution UAV Images.
Remote. Sens., 2022
Comparison of RFE-DL and stacking ensemble learning algorithms for classifying mangrove species on UAV multispectral images.
Int. J. Appl. Earth Obs. Geoinformation, 2022
2021
An Effective Method for Canopy Chlorophyll Content Estimation of Marsh Vegetation Based on Multiscale Remote Sensing Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021
Study on transfer learning ability for classifying marsh vegetation with multi-sensor images using DeepLabV3+ and HRNet deep learning algorithms.
Int. J. Appl. Earth Obs. Geoinformation, 2021
Comparison of optimized object-based RF-DT algorithm and SegNet algorithm for classifying Karst wetland vegetation communities using ultra-high spatial resolution UAV data.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2020
An Optimized Object-Based Random Forest Algorithm for Marsh Vegetation Mapping Using High-Spatial-Resolution GF-1 and ZY-3 Data.
Remote. Sens., 2020